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     "title": "MultiModal / Vision Language Models (BETA)",
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-    "text": "Dataset Format\nFor multi-modal datasets, we adopt an extended chat_template format similar to OpenAI’s Message format.\n\nA message is a list of role and content.\nrole can be system, user, assistant, etc.\ncontent is a list of type and (text or image or path or url or base64).\n\n\n\n\n\n\n\nNote\n\n\n\nFor backwards compatibility:\n\nIf the dataset has a images or image column of list[Image], it will be appended to the first content list as {\"type\": \"image\", \"image\": ...}. However, if the content already has a {\"type\": \"image\"} but no image key, it will be set the image key.\nIf content is a string, it will be converted to a list with type as text.\n\n\n\n\n\n\n\n\n\nTip\n\n\n\nFor image loading, you can use the following keys within content alongside \"type\": \"image\":\n\n\"path\": \"/path/to/image.jpg\"\n\"url\": \"https://example.com/image.jpg\"\n\"base64\": \"...\"\n\"image\": PIL.Image\n\n\n\nHere is an example of a multi-modal dataset:\n[\n  {\n    \"messages\": [\n        {\n            \"role\": \"system\",\n            \"content\": [\n              {\"type\": \"text\", \"text\": \"You are a helpful assistant.\"}\n              ]\n        },\n        {\n            \"role\": \"user\",\n            \"content\": [\n                {\"type\": \"image\", \"image\": \"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/bee.jpg\"},\n                {\"type\": \"text\", \"text\": \"Describe this image in detail.\"}\n            ]\n        },\n        {\n            \"role\": \"assistant\",\n            \"content\": [\n              {\"type\": \"text\", \"text\": \"The image is a bee.\"}\n            ]\n        }\n    ]\n  }\n]",
+    "text": "Dataset Format\nFor multi-modal datasets, we adopt an extended chat_template format similar to OpenAI’s Message format.\n\nA message is a list of role and content.\nrole can be system, user, assistant, etc.\ncontent is a list of type and (text or image or path or url or base64).\n\n\n\n\n\n\n\nNote\n\n\n\nFor backwards compatibility:\n\nIf the dataset has a images or image column of list[Image], it will be appended to the first content list as {\"type\": \"image\", \"image\": ...}. However, if the content already has a {\"type\": \"image\"} but no image key, it will be set the image key.\nIf content is a string, it will be converted to a list with type as text.\n\n\n\n\n\n\n\n\n\nTip\n\n\n\nFor image loading, you can use the following keys within content alongside \"type\": \"image\":\n\n\"path\": \"/path/to/image.jpg\"\n\"url\": \"https://example.com/image.jpg\"\n\"base64\": \"...\"\n\"image\": PIL.Image\n\n\n\nHere is an example of a multi-modal dataset:\n[\n  {\n    \"messages\": [\n        {\n            \"role\": \"system\",\n            \"content\": [\n              {\"type\": \"text\", \"text\": \"You are a helpful assistant.\"}\n              ]\n        },\n        {\n            \"role\": \"user\",\n            \"content\": [\n                {\"type\": \"image\", \"url\": \"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/bee.jpg\"},\n                {\"type\": \"text\", \"text\": \"Describe this image in detail.\"}\n            ]\n        },\n        {\n            \"role\": \"assistant\",\n            \"content\": [\n              {\"type\": \"text\", \"text\": \"The image is a bee.\"}\n            ]\n        }\n    ]\n  }\n]",
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